Data / BI Analyst Career Path

24 substantive modules, 96 guided activities and three synthetic-data portfolio projects. Native tool work requires compatible software.

Learn at your actual pace

Set independent minutes for each day, choose session and break lengths, and reserve a capacity buffer. Unfinished work rolls into available slots while completed evidence stays complete. The guided core is 4690 minutes; deeper practice is optional. No salary or hiring outcome is guaranteed.

Module 1: Clean data before calculating

A monthly collection report is only useful if every payment is counted once. All supplied names and amounts are fictional.

Module 2: Build conditional reporting rules

Your manager asks for January collections without accidentally including February.

Module 3: Look up attributes without hiding exceptions

Each payment needs its branch, but a wrong match would send collection credit to the wrong team.

Module 4: Deliver a target-versus-achievement MIS

Produce a January performance report that a branch manager can act on.

Module 5: Create a typed Power Query pipeline

Replace a monthly copy/paste ritual with a refreshable transformation.

Module 6: Make monthly refresh repeatable

Another analyst must be able to run your monthly report without asking where your files are.

Module 7: Query normalized tables safely

Answer a focused business question without changing production records.

Module 8: Aggregate KPIs with explicit denominators

A control report needs both the total and evidence that exceptions were not omitted.

Module 9: Join without multiplying balances

One loan has two January payments. A naive joined POS total is wrong even though every row is valid.

Module 10: Use CTEs as readable quality gates

Reviewers need to follow how raw payments become a trusted KPI table.

Module 11: Analyze sequence and month-on-month change

Compare recoveries over time without comparing a single event with an entire month.

Module 12: Present a reconciled SQL capstone

Deliver a query, results and explanation that another analyst can reproduce.

Module 13: Build a clear first Power BI report

Create a report that communicates the same checked totals as Excel and SQL.

Module 14: Model facts and dimensions deliberately

A report can show correct grand totals while giving wrong branch slices if relationships are ambiguous.

Module 15: Write context-aware DAX measures

The same measure must answer company, branch and month questions without hardcoded totals.

Module 16: Make the dashboard usable on a phone

Managers open reports on small screens, under time pressure and with different visual abilities.

Module 17: Compare periods without changing definitions

A rise in collected rupees is different from a rise in achievement percentage points.

Module 18: Make report quality operational

Your report must survive the next refresh and a different person operating it.

Module 19: Build the collections BI capstone

A fictional NBFC needs a compact collections dashboard and a defensible KPI dictionary.

Module 20: Tell a decision-ready story

A senior reviewer needs the decision, evidence and uncertainty in under a minute.

Module 21: Package factual career evidence

Translate your work into clear outcomes without exaggerating impact or skill level.

Module 22: Practice technical and stakeholder interviews

An interviewer is testing how you reason, not just whether you remember a function name.

Module 23: Run a focused job-search workflow

A small, current application list is more useful than hundreds of untracked submissions.

Module 24: Review evidence and plan the next 90 days

Finish by identifying what you can demonstrate and what still needs practice.

Interactive practice runs in your browser.